Computational finance models

The author discusses his involvement in developing computational finance software. These computational finance models attempt to model the randomness of a stock\´s price. At a fixed future time, a stock\´s price is modeled as a random variable with a normal distribution centered about the current price adjusted with a simple growth multiplier. The standard deviation of this normal distribution depends on the length of time into the future one peers and the volatility of the market. As the market becomes more volatile and we look further ahead, the less likely the stock will have a price near the adjusted current price. Implementing these ideas requires a tool borrowed from physics called the Brownian motion. In a sense, a stock\´s price is modeled as a point fluctuating about in "dollar space". Hence a financial modeler can no more predict what price a stock will have at a given instance in time than a physicist can predict where a particular air molecule might be.